German Longitudinal Election Study

The GLES for the 2025 early federal election


Categories: GLES

Following the dissolution of the German governing coalition on November 5, 2024, and the imminent vote of confidence by Chancellor Olaf Scholz, the GLES team at GESIS, in close collaboration with the board of the German Society for Electoral Research (DGfW), rapidly adapted the study design for GLES 2025 to accommodate an early federal election.

The GLES design for the 2025 federal election, which will presumably take place on February 23, 2025, features some important innovations compared to the GLES design for the last federal election in 2021:

The Pre-Election Cross-Section was combined with the Pre-Election of the Rolling Cross-Section (RCS). In addition, the planned sample size of the Post-Election Cross-Section, which will be conducted in a mixed-mode design with online (CAWI) and paper questionnaires (PAPI), was significantly increased. The RCS 2025 will be conducted online (CAWI) via a probabilistic online panel for the first time. Another novelty will be a supplementary wave before the election, and the re-interview after the election will also be conducted using an RCS design. The Panel will conduct three waves online (CAWI) before the election, one wave immediately after the election, and one wave on the formation of the government. The Tracking, conducted online (CAWI), will again consist of a pre-election survey for the federal election and another survey in late spring. In the Candidate Study, which is conducted in a mixed-mode design with online (CAWI) and paper questionnaires (PAPI), BSW candidates will be invited for the first time to be interviewed as part of a GLES federal election survey, and the Nomination Study will be conducted only using online research this time.

Detailed information on the GLES for the 2025 federal election can be found on 2025 Federal Election.

You can also receive GLES news and data releases via the GLES newsletter and GLES social media channels on Bluesky (@gles.bsky.social) and X (@gles_data).